import tensorflow as tf
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def himmelblau(x):
	return (x[0] ** 2 + x[1] - 11) ** 2 + (x[0] + x[1] ** 2 - 7) ** 2 

x = np.arange(-6, 6, 0.1)
y = np.arange(-6, 6, 0.1)

X, Y = np.meshgrid(x, y)

Z = himmelblau([X, Y])

fig = plt.figure("himmelblau")
ax = fig.gca(projection="3d")
ax.plot_surface(X, Y, Z)
ax.view_init(60, -30)
ax.set_xlabel("x")
ax.set_ylabel("y")
plt.show()


x = tf.constant([4., 0.])
for step in range(200):
	with tf.GradientTape() as tape:
		tape.watch([x])
		y = himmelblau(x)
	grads = tape.gradient(y, [x])[0]

	x -= 0.01 * grads
	if step % 20 == 19:
		print(f"step {step}: x = {x.numpy()}, f(x) = {y.numpy()}")